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A Hybrid Model for Lake Powell Inflow Prediction
  • Samuel Edwin Potteiger,
  • Xubin Zeng
Samuel Edwin Potteiger
University of Arizona

Corresponding Author:[email protected]

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Xubin Zeng
University of Arizona
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Abstract

Lake Powell is a major reservoir responsible for providing water resources throughout the Colorado River Basin. Here we develop a hybrid model to perform 1-4 month forecasts of the inflow to Lake Powell. First, observational data are used in early December for a binary prediction of high- or low-flow based on peak monthly inflow or April-July inflow, and our prediction is much better than the Colorado Basin River Forecast Center (CBRFC)’s forecasts for the 1982-2016 study period. Second, we calibrate the NCEP Climate Forecast System seasonal forecasts of temperature, precipitation, and snow mass, and use them to perform 1-4 month inflow prediction through a regression equation, with the coefficients determined for the high- and low-flow years separately. Our early April forecasts for the critical April-July inflow are better than those of the CBRFC from 1982-2016. Sensitivity tests have also demonstrated the value of including snow mass in our prediction.